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Machine Learning & Computer Vision Engineer

Machine Learning & Computer Vision Engineer

AtkinsRéalis

11 - 12 years

35 - 45 Lacs

hyderabad

Posted:4 hours ago| Platform:

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Skills Required

digital analysts balance sheet forecasting gst auditing accounting internal audit artificial intelligence sales account management marketing saas relationship management tally erp accounts finalisation tally taxation staff augmentation finance ml

Work Mode

Work from Office

Job Type

Full Time

Job Description

We re AtkinsR alis, a world class Engineering Services and Nuclear organization. We connect people, data and technology to transform the worlds infrastructure and energy systems. Together, with our industry partners and clients, and our global team of consultants, designers, engineers and project managers, we can change the world. Created by the integration of long-standing organizations dating back to 1911, we are a world-leading professional services company dedicated to engineering a better future for our planet and its people. We deploy global capabilities locally to our clients and deliver unique end-to-end services across the whole life cycle of an asset including consulting, advisory environmental services, intelligent networks cybersecurity, design engineering, procurement, project construction management, operations maintenance, decommissioning and capital. The breadth and depth of our capabilities are delivered to clients in key strategic sectors.

Key Responsibilities:

Data Collection Pipeline Development:
- Collect and curate a large-scale dataset of urban, architectural, and interior design images, including floor plans, room scenes, building exteriors, and construction details.
- Develop robust data pipelines for preprocessing (resizing, labeling styles or room types, tagging materials, etc.) to ensure high-quality, domain-relevant training data.
- Maintain data versioning and augmentation pipelines to boost model robustness and ensure traceability.
Model Training Optimization:
- Lead the implementation of the end-to-end training pipeline, including GPU setup (cloud or on-premise), training workflows, and runtime optimization.
- Train and fine-tune generative models and computer vision systems, monitoring performance and adjusting parameters for maximum quality and efficiency.
Deployment MLOps:
- Deploy trained models into production environments (cloud APIs or integrations within design software).
- Establish MLOps practices for continuous integration of model updates, automated retraining, model version control, and CI/CD for ML services.
- Optimize model inference (quantization, model compression) to deliver low-latency, high-reliability performance to end-users.

Evaluation Quality Assurance:
- Work with the AI Research Scientist and Product/Design Lead to test model outputs and ensure alignment with architectural design standards.
- Implement evaluation metrics that reflect domain needs e.g., accuracy of architectural details, style coherence, or alignment with user-specified parameters.
Required Qualifications:
- Master s degree in Computer Science, Data Science, or a related field (or strong practical experience equivalent).
- Proficiency in Python (and possibly C++ for performance-critical components). Experience in building robust data and ML pipelines using frameworks such as Pandas, NumPy, and cloud data storage for handling millions of images.
- ML Expertise: Hands-on experience training deep learning models for images, with knowledge of MLOps tools and best practices e.g., MLflow or Kubeflow for experiment tracking, Docker for containerization, and continuous deployment.
- Strong understanding of image augmentation, CNNs, and evaluation metrics (FID, precision/recall) for generative models. Familiarity with generative AI frameworks such as Stable Diffusion, GAN libraries, or vision transformers.
- Domain Familiarity: Understanding of urban, architecture, and interior design datasets and workflows is a significant plus.
Relevant Experience/Background:
- Full Lifecycle ML Projects: Prior experience taking a machine learning project from problem definition and data preparation to model training, deployment, and monitoring in production.
- Large-Scale Data Handling: Experience managing datasets of hundreds of thousands or more images where data volume and pipeline reliability were critical (e.g., imaging company, autonomous driving dataset, or large content platform).
- AEC/Design Tech: Experience specifically in the architecture, engineering, construction (AEC) or design technology field is highly valuable, understanding CAD/BIM data or architectural imagery workflows helps ensure better model performance.
- Software/DevOps: History of building reliable web services or tools (not just ML prototypes), indicating the ability to create a stable, production-grade AI platform.

What We Can Offer You:

Varied, interesting and meaningful work.
A hybrid working environment with flexibility and great opportunities.
Opportunities for training and, as the team grows, career progression or sideways moves.
An opportunity to work within a large global multi-disciplinary consultancy on a mission to change the ways we approach business as usual.

Why work for AtkinsR alis

Link: Equality, diversity inclusion | Atkins India (atkinsrealis.com)

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Machine Learning & Computer Vision Engineer